Developers and administrators often seek detailed “analytics data” specifying, in a quantitative manner, how various aspects of an application are being used by the end-user. Such analytics data—which typically track whether and to what extent certain buttons, links, and other user interface elements are used—may be provided in the form of an “analytics dashboard.” An analytics dashboard typically displays a collection of charts, lists, and graphs representing data received from an analytics server, allowing the analyst (e.g., a developer or administrator) to select a data range based on time, application version, and the like.
While traditional “dashboard” user interfaces are effective in providing a detailed account of how a particular application is being used, it can be difficult for a developer to visualize, intuitively, the way that users are navigating through a particular application. For example, analytics data for a typical mobile app might include hundreds of “event labels” (e.g., “button1_click,” “button2_click,” etc.), but association between these event labels and elements of the actual application is often not clear when viewing such data in a traditional analytics dashboard. Furthermore, it can be challenging to view a dashboard user interface on mobile devices of the type having relatively small displays.
Accordingly, methods and systems are desired for improved user interfaces for displaying analytics data.